Abstract

Current trends in electrification of the final energy consumption and towards a massive electricity production from renewables are leading a revolution in the electric distribution system. Indeed, the traditional “fit & forget” planning approach used by Distributors would entail a huge amount of network investment. Therefore, for making these trends economically sustainable, the concept of Smart Distribution Network has been proposed, based on active management of the system and the exploitation of flexibility services provided by Distributed Energy Resources. However, the uncertainties associated to this innovation are holding its acceptance by utilities. For increasing their confidence, new risk-based planning tools are necessary, able to estimate the residual risk connected with each choice and identify solutions that can gradually lead to a full Smart Distribution Network implementation. Battery energy storage systems, owned and operated by Distributors, represent one of these solutions, since they can support the use of local flexibility services by covering part of the associated uncertainties. The paper presents a robust approach for the optimal exploitation of these flexibility services with a simultaneous optimal allocation of storage devices. For each solution, the residual risk is estimated, making this tool ready for its integration within a risk-based planning procedure.

Highlights

  • With the ambition of achieving a net-zero greenhouse gas emissions by 2050, European Union planned several actions aimed at realizing high shares of renewable energy use (28% by 2030 and 66% by 2050) and of heat and transport electrification [1,2]

  • Despite the COVID-19 pandemic has caused a fall in electricity consumption [3], the power generation from renewable energy sources (RES) continues its accelerating expansion [4], keeping valid the general goal of increasing loading and hosting capacity of the electric distribution systems

  • The second calculation, coupled to the optimal exploitation of flexibility services from Distributed Energy Resources (DERs), is deeply illustrated in Section 4 and constitutes the main novelty of the paper. This procedure is based on a Robust Linear Programming (RLP) for modelling the uncertainties related to the active management of DER and estimating the residual risk associated to each optimal solution identified

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Summary

Introduction

With the ambition of achieving a net-zero greenhouse gas emissions by 2050, European Union planned several actions aimed at realizing high shares of renewable energy use (28% by 2030 and 66% by 2050) and of heat and transport electrification (exceeding 50% by 2050) [1,2]. The second calculation, coupled to the optimal exploitation of flexibility services from DERs, is deeply illustrated in Section 4 and constitutes the main novelty of the paper This procedure is based on a Robust Linear Programming (RLP) for modelling the uncertainties related to the active management of DER and estimating the residual risk associated to each optimal solution identified. To reduce the uncertainty of the flexibility services provision, the DSO has the possibility to install and operate some Battery Energy Storage Systems (BESSs) For this reason, the objective function of the RLP has been built to find the optimal rate and location of these devices, identifying an economic balance between flexibility services exploitation and BESS investment.

Robust Optimization
Risk Assessment of Technical Constraints Violation
Case Study
Results and Discussion
Single Hour Analysis
Full Text
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